Research Areas

During my PhD studies, I have worked/currently worked on both financial mathematical questions and mathematical foundations of machine learning techniques. In particular, I tried to address problems arising from financial questions with solutions involving machine learning. Moreover, due to my mathematical background, I tried to study those techniques from a mathematical point of view to not only apply but also understand them in depth. Over the last three years, I worked on:

• Rough Volatility Models
• Application of Neural Network Approximation in Finance
• Randomised Signatures/Reservoir Computing

Articles

The following documents predominantly address topics I wanted to understand in the past, and I typed them up in a way that I deemed to be the clearest. Maybe they are helpful for someone out there. Of course, although they are written by me, the content is in general no new research.

• Solution to Optiver's Signal Problem
• Applications of Orthogonal Projections
• Introduction to the Math of Deep Learning and GANs
• Overview of Most Common Sorting Algortihms